Sift Client Basic Usage¶

This notebook demonstrates the core features of the Sift Python client:

• Initializing the Sift client
• Finding, creating, and updating resources
• Searching channels
• Pulling data
• Creating calculated channels

Running this notebook¶

This notebook is written in Jupyter Notebook format and can be run in any Jupyter environment.

Some additional package prerequisites are required to run this notebook

• notebook for running Jupyter Notebooks
• python-dotenv for loading environment variables
• rich for pretty-printing output
• pandas for data manipulation and analysis
• matplotlib for data visualization

You can install these packages using pip install notebook rich python-dotenv pandas matplotlib.

Setup and Initialization¶

First, import the necessary modules and initialize the Sift client with your credentials.

Best practice is to access credentials using environment variables or a .env file with python-dotenv. Avoid hardcoding your API in any code you write.

In [41]:

import os
from datetime import datetime, timedelta

from dotenv import load_dotenv
from rich import print
from sift_client import SiftClient

import os from datetime import datetime, timedelta from dotenv import load_dotenv from rich import print from sift_client import SiftClient

In [42]:

# Get our environment variables
load_dotenv()  # Load environment variables from .env file
api_key = os.getenv("SIFT_API_KEY")
grpc_url = os.getenv("SIFT_GRPC_URI")
rest_url = os.getenv("SIFT_REST_URI")

client = SiftClient(api_key=api_key, grpc_url=grpc_url, rest_url=rest_url)

print("✓ Sift client initialized successfully")

# Get our environment variables load_dotenv() # Load environment variables from .env file api_key = os.getenv("SIFT_API_KEY") grpc_url = os.getenv("SIFT_GRPC_URI") rest_url = os.getenv("SIFT_REST_URI") client = SiftClient(api_key=api_key, grpc_url=grpc_url, rest_url=rest_url) print("✓ Sift client initialized successfully")

✓ Sift client initialized successfully

Sift Resources¶

Sift objects, such as Assets, Runs, etc. are all accessed via their API resources.

The SiftClient class provides these resources as properties

• assets
• runs
• etc.

Asynchronous versions are also available by accessing the async_ property of the client. For example

• client.async_.assets
• client.async_.runs
• etc.

For example, the Ping resource can be used for a basic health check.

In [55]:

client.ping.ping()

client.ping.ping()

Out[55]:

'Hello from Sift!'

Assets and Runs¶

Assets represent physical or logical entities in your system (e.g., vehicles, machines, devices). Runs represent time-bounded operational periods for an asset (e.g., a flight, a test, a mission).

Resources generally offer similar interaction patterns and methods. For example, the AssetsAPI has

• get
• list_
• find
• update
• archive
• unarchive

Other resources may offer additional methods such as create.

These resource methods operate on and will return Sift object types. More on tehse can be found here: sift_types

Listing, Finding, and Getting¶

list_ can be used to retrieve objects that match a specific set of criteria:

In [44]:

# List all assets (limited to 10 for this example)
assets = client.assets.list_(name_contains="Mars", limit=5)
for asset in assets:
    print(f"Name: {asset.name}, ID: {asset.id_}")

# List all assets (limited to 10 for this example) assets = client.assets.list_(name_contains="Mars", limit=5) for asset in assets: print(f"Name: {asset.name}, ID: {asset.id_}")

Name: MarsRoverIngestPusher, ID: 429b864b-0911-4e23-b9d1-2a1fba4d441c

Name: Mars Rover [Jonno export test], ID: 5d86ed46-dec6-41c8-8680-a0ba02d9e546

Name: MarsRover_pb4, ID: 9bb3bfec-840d-40b7-a5ab-25591f9a1b38

Name: MarsRover, ID: 611914d3-ffb1-402e-ae1e-5eb3e66dea7c

Name: MarsRover42NaN, ID: 0ad88099-1aea-461c-91b5-0a91c7811f74

find can be used to find a single matching object. It will return an error if multiple are found. It takes the same arguments and filters as list_.

In [45]:

# Find a specific asset by name
asset_name = "MarsRover0"
asset = client.assets.find(name=asset_name)
print(asset)

# Find a specific asset by name asset_name = "MarsRover0" asset = client.assets.find(name=asset_name) print(asset)

Asset(
    id_='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    name='MarsRover0',
    organization_id='dd9f82ef-7805-4b02-9572-ec61b71edde6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    tags=['simulator', 'speed-test'],
    metadata={'vehicle_type': 'rover', 'vehicle_version': 123123123.0, 'version_active': True},
    is_archived=False,
    archived_date=datetime.datetime(1970, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)
)

When we know exactly what we are looking for, we can use get.

In [46]:

# Get the exact asset by ID
asset = client.assets.get(asset_id=asset.id_)
print(asset)

# Get the exact asset by ID asset = client.assets.get(asset_id=asset.id_) print(asset)

Asset(
    id_='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    name='MarsRover0',
    organization_id='dd9f82ef-7805-4b02-9572-ec61b71edde6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    tags=['simulator', 'speed-test'],
    metadata={'vehicle_type': 'rover', 'vehicle_version': 123123123.0, 'version_active': True},
    is_archived=False,
    archived_date=datetime.datetime(1970, 1, 1, 0, 0, tzinfo=datetime.timezone.utc)
)

Creating, Updating, and Archiving¶

Most resources offer create, update, and archive methods.

Since create returns a Run, we can chain update and archive on it and the Sift object will update in-place.

In [47]:

# Run creation
run = client.runs.create(
    dict(
        name="Test Run", description="A test run", asset_ids=[asset.id_], start_time=datetime.now()
    )
)
print(run)

# Run creation run = client.runs.create( dict( name="Test Run", description="A test run", asset_ids=[asset.id_], start_time=datetime.now() ) ) print(run)

Run(
    id_='523c6f2a-181c-4ee7-8876-421901daf97f',
    name='Test Run',
    description='A test run',
    created_date=datetime.datetime(2025, 10, 10, 21, 43, 39, 913134, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 10, 10, 21, 43, 39, 915093, tzinfo=datetime.timezone.utc),
    created_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c',
    modified_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c',
    organization_id='dd9f82ef-7805-4b02-9572-ec61b71edde6',
    metadata={},
    tags=[],
    asset_ids=[],
    is_adhoc=False,
    is_archived=False,
    start_time=datetime.datetime(2025, 10, 10, 14, 43, 39, 861550, tzinfo=datetime.timezone.utc),
    stop_time=None,
    duration=datetime.timedelta(seconds=25200, microseconds=54929),
    default_report_id='854787b6-4e38-4c81-bdf0-8d143c791d01',
    client_key=None,
    archived_date=None
)

In [48]:

# Run update
run.update(
    dict(
        name="Updated Test Run",
        description="An updated test run",
    )
)
print(run)

# Run update run.update( dict( name="Updated Test Run", description="An updated test run", ) ) print(run)

Run(
    id_='523c6f2a-181c-4ee7-8876-421901daf97f',
    name='Updated Test Run',
    description='An updated test run',
    created_date=datetime.datetime(2025, 10, 10, 21, 43, 39, 913134, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 10, 10, 21, 43, 39, 981793, tzinfo=datetime.timezone.utc),
    created_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c',
    modified_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c',
    organization_id='dd9f82ef-7805-4b02-9572-ec61b71edde6',
    metadata={},
    tags=[],
    asset_ids=[],
    is_adhoc=False,
    is_archived=False,
    start_time=datetime.datetime(2025, 10, 10, 14, 43, 39, 861550, tzinfo=datetime.timezone.utc),
    stop_time=None,
    duration=datetime.timedelta(seconds=25200, microseconds=123957),
    default_report_id='854787b6-4e38-4c81-bdf0-8d143c791d01',
    client_key=None,
    archived_date=None
)

In [49]:

# Run archive
run.archive()
print(run)

# Run archive run.archive() print(run)

Run(
    id_='523c6f2a-181c-4ee7-8876-421901daf97f',
    name='Updated Test Run',
    description='An updated test run',
    created_date=datetime.datetime(2025, 10, 10, 21, 43, 39, 913134, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 10, 10, 21, 43, 40, 52001, tzinfo=datetime.timezone.utc),
    created_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c',
    modified_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c',
    organization_id='dd9f82ef-7805-4b02-9572-ec61b71edde6',
    metadata={},
    tags=[],
    asset_ids=[],
    is_adhoc=False,
    is_archived=True,
    start_time=datetime.datetime(2025, 10, 10, 14, 43, 39, 861550, tzinfo=datetime.timezone.utc),
    stop_time=None,
    duration=datetime.timedelta(seconds=25200, microseconds=196350),
    default_report_id='854787b6-4e38-4c81-bdf0-8d143c791d01',
    client_key=None,
    archived_date=datetime.datetime(2025, 10, 10, 21, 43, 40, 48186, tzinfo=datetime.timezone.utc)
)

Searching Channels¶

Channels represent time-series data streams (e.g., sensor readings, telemetry).

In [50]:

# List channels for the selected asset
channels = client.channels.list_(asset=asset.id_, limit=5)

print(f"Found {len(channels)} channels for asset '{asset.name}':")
for channel in channels:  # Show first 10
    print(channel)

# List channels for the selected asset channels = client.channels.list_(asset=asset.id_, limit=5) print(f"Found {len(channels)} channels for asset '{asset.name}':") for channel in channels: # Show first 10 print(channel)

Found 5 channels for asset 'MarsRover0':

Channel(
    id_='0f1a32d4-0f97-494f-82f8-2ed7f3983e74',
    name='is_even',
    data_type=<ChannelDataType.BOOL: 5>,
    description='is the value of milliseconds even',
    unit='0c359676-c6c9-47d3-acca-d8e938311b2a',
    bit_field_elements=[],
    enum_types={},
    asset_id='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d'
)

Channel(
    id_='1c2dd815-2c9e-4801-92dc-1f65cad2114b',
    name='voltage',
    data_type=<ChannelDataType.INT_32: 7>,
    description='voltage at the source',
    unit='09f1005b-df6a-4f82-838f-c57e77c587ef',
    bit_field_elements=[],
    enum_types={},
    asset_id='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d'
)

Channel(
    id_='606817a0-396e-4575-9ffc-45a4ef9ca66a',
    name='log',
    data_type=<ChannelDataType.STRING: 2>,
    description='this simulates log files',
    unit='0c359676-c6c9-47d3-acca-d8e938311b2a',
    bit_field_elements=[],
    enum_types={},
    asset_id='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d'
)

Channel(
    id_='a59c4ec4-5e8c-4457-8a41-ecbc06b0dca7',
    name='mainmotor.velocity',
    data_type=<ChannelDataType.DOUBLE: 1>,
    description='speed',
    unit='b840c8e8-33fb-433c-9448-07577f04e990',
    bit_field_elements=[],
    enum_types={},
    asset_id='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d'
)

Channel(
    id_='c052cef4-d3eb-486e-b3cb-63b59504e913',
    name='gpio',
    data_type=<ChannelDataType.BIT_FIELD: 4>,
    description='on/off values for pins on gpio',
    unit='0c359676-c6c9-47d3-acca-d8e938311b2a',
    bit_field_elements=[
        {'name': '12v', 'index': 0, 'bit_count': 1},
        {'name': 'charge', 'index': 1, 'bit_count': 2},
        {'name': 'led', 'index': 3, 'bit_count': 4},
        {'name': 'heater', 'index': 7, 'bit_count': 1}
    ],
    enum_types={},
    asset_id='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d'
)

In [51]:

# Search for specific channels by name pattern
# Replace with a pattern that matches your channel names
velocity_channels = client.channels.list_(asset=asset.id_, name_contains="velocity", limit=10)

print(f"Channels containing 'velocity': {len(velocity_channels)}")
for ch in velocity_channels:
    print(ch)

# Search for specific channels by name pattern # Replace with a pattern that matches your channel names velocity_channels = client.channels.list_(asset=asset.id_, name_contains="velocity", limit=10) print(f"Channels containing 'velocity': {len(velocity_channels)}") for ch in velocity_channels: print(ch)

Channels containing 'velocity': 1

Channel(
    id_='a59c4ec4-5e8c-4457-8a41-ecbc06b0dca7',
    name='mainmotor.velocity',
    data_type=<ChannelDataType.DOUBLE: 1>,
    description='speed',
    unit='b840c8e8-33fb-433c-9448-07577f04e990',
    bit_field_elements=[],
    enum_types={},
    asset_id='61d6e4f0-8287-4678-b071-18a95fcd9db6',
    created_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 3, 4, 19, 51, 15, 89746, tzinfo=datetime.timezone.utc),
    created_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d',
    modified_by_user_id='f47e4854-234b-421c-badb-7f8bb757cd9d'
)

In [52]:

# Get channels for a specific run. There should be none since we just created it.
if run:
    run_channels = client.channels.list_(run=run.id_, limit=10)
    print(f"Channels in run '{run.name}': {len(run_channels)}")
    for ch in run_channels:
        print(f"  - {ch.name}")

# Get channels for a specific run. There should be none since we just created it. if run: run_channels = client.channels.list_(run=run.id_, limit=10) print(f"Channels in run '{run.name}': {len(run_channels)}") for ch in run_channels: print(f" - {ch.name}")

Channels in run 'Updated Test Run': 0

Pulling Data¶

Retrieve time-series data from channels as pandas DataFrames.

In [53]:

run = client.runs.list_(
    duration_greater_than=timedelta(seconds=30),
    description_contains="simulated run: 1 flows, 8 total channels, 5hz sampling rate",
)[0]

# Get data as a dictionary of pandas DataFrames
data = client.channels.get_data(
    channels=client.channels.list_(run=run, name_contains="v"),
    run=run,
    limit=1000,  # Limit to 1000 data points per channel
)

print(f"\n✓ Retrieved data for {len(data)} channels:")
for channel_name, df in data.items():
    print(f"\n  Channel: {channel_name}")
    print(f"  Data points: {len(df)}")
    print(df.head())

run = client.runs.list_( duration_greater_than=timedelta(seconds=30), description_contains="simulated run: 1 flows, 8 total channels, 5hz sampling rate", )[0] # Get data as a dictionary of pandas DataFrames data = client.channels.get_data( channels=client.channels.list_(run=run, name_contains="v"), run=run, limit=1000, # Limit to 1000 data points per channel ) print(f"\n✓ Retrieved data for {len(data)} channels:") for channel_name, df in data.items(): print(f"\n Channel: {channel_name}") print(f" Data points: {len(df)}") print(df.head())

✓ Retrieved data for 4 channels:

  Channel: is_even

  Data points: 1000

                                     is_even
2025-06-04 17:21:13.180486958+00:00     True
2025-06-04 17:21:13.380486958+00:00     True
2025-06-04 17:21:13.580486958+00:00     True
2025-06-04 17:21:13.780486958+00:00     True
2025-06-04 17:21:13.980486958+00:00     True

  Channel: mainmotor.velocity

  Data points: 1000

                                     mainmotor.velocity
2025-06-04 17:21:13.180486958+00:00           21.352492
2025-06-04 17:21:13.380486958+00:00           32.011998
2025-06-04 17:21:13.580486958+00:00           34.370449
2025-06-04 17:21:13.780486958+00:00           25.635827
2025-06-04 17:21:13.980486958+00:00           16.148490

  Channel: vehicle_state

  Data points: 1000

                                     vehicle_state
2025-06-04 17:21:13.180486958+00:00              1
2025-06-04 17:21:13.380486958+00:00              1
2025-06-04 17:21:13.580486958+00:00              1
2025-06-04 17:21:13.780486958+00:00              1
2025-06-04 17:21:13.980486958+00:00              1

  Channel: voltage

  Data points: 1000

                                     voltage
2025-06-04 17:21:13.180486958+00:00       12
2025-06-04 17:21:13.380486958+00:00       12
2025-06-04 17:21:13.580486958+00:00       12
2025-06-04 17:21:13.780486958+00:00        2
2025-06-04 17:21:13.980486958+00:00        2

Creating Calculated Channels¶

Calculated channels allow you to create derived metrics from existing channels using mathematical expressions.

In [58]:

# Create a calculated channel
# This example creates a channel that divides two existing channels
# Replace channel names with actual channels from your system


# Use first two channels for this example
channel1 = channels[0]
channel2 = channels[1]

calc_channel_name = f"{channel1.name}_per_{channel2.name}"

# Check if calculated channel already exists
existing = client.calculated_channels.find(
    name=calc_channel_name, asset=asset.id_, include_archived=True
)

if existing:
    print(f"Calculated channel '{calc_channel_name}' already exists")
    calc_channel = existing
else:
    print(f"Creating calculated channel: {calc_channel_name}")

    calc_channel = client.calculated_channels.create(
        dict(
            name=calc_channel_name,
            description=f"Ratio of {channel1.name} to {channel2.name}",
            expression="$1 / $2",  # $1 and $2 refer to the channel references below
            expression_channel_references=[
                dict(channel_reference="$1", channel_identifier=channel1.name),
                dict(channel_reference="$2", channel_identifier=channel2.name),
            ],
            asset_ids=[asset.id_],
        )
    )

print(calc_channel)

# Create a calculated channel # This example creates a channel that divides two existing channels # Replace channel names with actual channels from your system # Use first two channels for this example channel1 = channels[0] channel2 = channels[1] calc_channel_name = f"{channel1.name}_per_{channel2.name}" # Check if calculated channel already exists existing = client.calculated_channels.find( name=calc_channel_name, asset=asset.id_, include_archived=True ) if existing: print(f"Calculated channel '{calc_channel_name}' already exists") calc_channel = existing else: print(f"Creating calculated channel: {calc_channel_name}") calc_channel = client.calculated_channels.create( dict( name=calc_channel_name, description=f"Ratio of {channel1.name} to {channel2.name}", expression="$1 / $2", # $1 and $2 refer to the channel references below expression_channel_references=[ dict(channel_reference="$1", channel_identifier=channel1.name), dict(channel_reference="$2", channel_identifier=channel2.name), ], asset_ids=[asset.id_], ) ) print(calc_channel)

Calculated channel 'is_even_per_voltage' already exists

CalculatedChannel(
    id_='d283b5fe-fed5-4260-93d1-8bd65bec4bfe',
    name='is_even_per_voltage',
    description='Ratio of is_even to voltage',
    expression='$1 / $2',
    channel_references=[
        {'channel_reference': '$1', 'channel_identifier': 'is_even'},
        {'channel_reference': '$2', 'channel_identifier': 'voltage'}
    ],
    is_archived=True,
    units='',
    asset_ids=['61d6e4f0-8287-4678-b071-18a95fcd9db6'],
    tag_ids=[],
    all_assets=False,
    organization_id='dd9f82ef-7805-4b02-9572-ec61b71edde6',
    client_key='',
    archived_date=datetime.datetime(2025, 10, 10, 21, 36, 19, 947790, tzinfo=datetime.timezone.utc),
    version_id='0923ec64-9799-4e73-8038-71496227a846',
    version=1,
    change_message='Created calculated channel',
    user_notes='',
    created_date=datetime.datetime(2025, 10, 10, 21, 34, 3, 533939, tzinfo=datetime.timezone.utc),
    modified_date=datetime.datetime(2025, 10, 10, 21, 34, 3, 533939, tzinfo=datetime.timezone.utc),
    created_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c',
    modified_by_user_id='ae1f6c7c-3e93-40a9-8796-d227a725662c'
)

In [25]:

# List all calculated channels for the asset
calc_channels = client.calculated_channels.list_(asset=asset.id_, name=calc_channel_name, limit=10)

print(f"Calculated channels for asset '{asset.name}': {len(calc_channels)}")
for cc in calc_channels:
    print(f"  - {cc.name}")
    print(f"    Expression: {cc.expression}")
    print(f"    Version: {cc.version}")

# List all calculated channels for the asset calc_channels = client.calculated_channels.list_(asset=asset.id_, name=calc_channel_name, limit=10) print(f"Calculated channels for asset '{asset.name}': {len(calc_channels)}") for cc in calc_channels: print(f" - {cc.name}") print(f" Expression: {cc.expression}") print(f" Version: {cc.version}")

Calculated channels for asset 'MarsRover0': 1

  - is_even_per_voltage

    Expression: $1 / $2

    Version: 1

In [26]:

# Optional: Clean up resources
# Uncomment to archive the created calculated channel and rule

if calc_channel:
    calc_channel.archive()
    print(f"Archived calculated channel: {calc_channel.name}")

print("\n✓ Example complete!")

# Optional: Clean up resources # Uncomment to archive the created calculated channel and rule if calc_channel: calc_channel.archive() print(f"Archived calculated channel: {calc_channel.name}") print("\n✓ Example complete!")

Archived calculated channel: is_even_per_voltage

✓ Example complete!